Fix blockwise coregistration direction

.gitignore

@@ -153,5 +153,6 @@ doc/source/gen_modules/
 doc/source/sg_execution_times.rst
 examples/basic/temp.tif
 
-# Directory where myst_nb executes jupyter code
+# Directory where myst_nb executes jupyter code and cache
 doc/jupyter_execute/
+doc/.jupyter_cache/

doc/source/coregistration.md

@@ -495,17 +495,22 @@ For instance, for {class}`xdem.coreg.Deramp`, an input `poly_order` to define th
 for {class}`xdem.coreg.DirectionalBias`, an input `angle` to define the angle at which to do the directional correction.
 
 ## Dividing coregistration in blocks
- 
+
 ### The {class}`~xdem.coreg.BlockwiseCoreg` object
-
-Sometimes, we want to split a coregistration across different spatial subsets of an elevation dataset, running that 
+
+```{caution}
+The {class}`~xdem.coreg.BlockwiseCoreg` feature is still experimental: it might not support all coregistration
+methods, and create edge artefacts.
+```
+
+Sometimes, we want to split a coregistration across different spatial subsets of an elevation dataset, running that
 method independently in each subset. A {class}`~xdem.coreg.BlockwiseCoreg` can be constructed for this:
 
 ```{code-cell} ipython3
 blockwise = xdem.coreg.BlockwiseCoreg(xdem.coreg.NuthKaab(), subdivision=16)
 ```
 
-The subdivision corresponds to an equal-length block division across the extent of the elevation dataset. It needs 
+The subdivision corresponds to an equal-length block division across the extent of the elevation dataset. It needs
 to be a number of the form 2{sup}`n` (such as 4 or 256).
 
 It is run the same way as other coregistrations:
@@ -528,4 +533,4 @@ ax[0].set_title("Before block NK")
 ax[1].set_title("After block NK")
 (aligned_dem - ref_dem).plot(cmap='RdYlBu', vmin=-30, vmax=30, ax=ax[1], cbar_title="Elevation differences (m)")
 _ = ax[1].set_yticklabels([])
-```
+```

tests/test_coreg/test_base.py

@@ -950,7 +950,7 @@ def test_blockwise_coreg_large_gaps(self) -> None:
         ddem_post = (aligned - self.ref).data.compressed()
         ddem_pre = (tba - self.ref).data.compressed()
         assert abs(np.nanmedian(ddem_pre)) > abs(np.nanmedian(ddem_post))
-        # assert np.nanstd(ddem_pre) > np.nanstd(ddem_post)
+        assert np.nanstd(ddem_pre) > np.nanstd(ddem_post)
 
 
 class TestAffineManipulation:

xdem/coreg/base.py

@@ -3393,8 +3393,8 @@ def _apply_rst(
         warped_dem = warp_dem(
             dem=elev,
             transform=transform,
-            source_coords=all_points[:, :, 0],
-            destination_coords=all_points[:, :, 1],
+            source_coords=all_points[:, :, 1],
+            destination_coords=all_points[:, :, 0],
             resampling="linear",
         )
 
@@ -3538,7 +3538,7 @@ def warp_dem(
     if not no_vertical:
         grid_offsets = scipy.interpolate.griddata(
             points=destination_coords_scaled[:, :2],
-            values=destination_coords_scaled[:, 2] - source_coords_scaled[:, 2],
+            values=source_coords_scaled[:, 2] - destination_coords_scaled[:, 2],
             xi=(grid_x, grid_y),
             method=resampling,
             fill_value=np.nan,